EEM762 Advanced Control Systems lecture notes from: Advanced Control Engineering, Laurent Lessard weekly schedule week part topic 1 linear algebra and basic optimization introduction and math review; least squares 2 linear algebra and basic optimization least norm optimization; multi-objective optimization 3 linear algebra and basic optimization singular value decomposition (SVD); properties of the SVD; uncertainty ellipsoids 4 optimal estimation and control random variables and vectors; marginal and conditional distributions; joint distribution and estimation 5 optimal estimation and control Kalman filter; steady-state Kalman filter 6 optimal estimation and control linear quadratic regulator (LQR), stochastic LQR 7 review and preparation for the exam (midterm) 8 midterm exam 9 optimal estimation and control balanced realization, linear quadratic Gaussian (LQG) control 10 constrained optimization convex optimization, bounding and duality 11 constrained optimization Karush-Kuhn-Tucker (KKT) conditions 12 constrained and robust control model predictive control 13 constrained and robust control Lyapunov stability theory 14 constrained and robust control H2 and Hinf norms; risk-sensitive control; the S-procedure 15 review and preparation for the exam (final) Previous Next Leave a Comment
EEE465 Numerical Methods for Artificial Intelligence lecture notes from: Matrix Methods in Machine Learning, Laurent Lessard
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